GOT-10k Evaluation Server

Submit your tracking results on GOT-10k to this website and evaluate the performance. Leaderboard will be updated immediately once the results are evaluated.

Tracker

Short Name:

SeqTrackV1

Long Name:

Sequence to Sequence Learning for Visual Object Tracking

Method Description:

seqtrack_b256_got

Project Page:

https://github.com/microsoft/VideoX/tree/master/SeqTrack

Paper URL:

None

Code URL:

None

Hardware:

NVIDIA GeForce RTX 4090

Language:

Python

Author:

THEATLAS

LaTex Bibtex:

@InProceedings{Chen_2023_CVPR, author = {Chen, Xin and Peng, Houwen and Wang, Dong and Lu, Huchuan and Hu, Han}, title = {SeqTrack: Sequence to Sequence Learning for Visual Object Tracking}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, month = {June}, year = {2023}, pages = {14572-14581} }

Legend:

None

Submissions

Submmition Count:

1 submissions.

Performance:

Method AO SR0.50 SR0.75 Hz Hardware Language Date↓ Reports
1 SeqTrackV1 0.747 0.847 0.718 27.55 fps NVIDIA GeForce RTX 4090 Python 2024-05-08, 05:09:57 reports.json